U.S. patent number 6,438,194 [Application Number 09/761,250] was granted by the patent office on 2002-08-20 for method of and device for forming x-ray images.
This patent grant is currently assigned to Koninklijke Philips Electronics. N.V.. Invention is credited to Michael Grass, Geerd Richard Kemkers.
United States Patent |
6,438,194 |
Grass , et al. |
August 20, 2002 |
Method of and device for forming X-ray images
Abstract
The invention relates to a method of forming X-ray images (B)
from at least two series of projection data sets (P.sub.1, P.sub.2)
successively acquired along different trajectories (T.sub.1,
T.sub.2), a respective 3D data set (S.sub.1, S.sub.2) being formed
from each series of projection data sets (P.sub.1, P.sub.2). In
order to neutralize motions of the patient between the acquisition
of the individual series of projection data sets upon combination
of the 3D data sets so as to form X-ray images which are as free
from artefacts as possible, the invention proposes to determine a
transformation rule (F) describing the location in space of the 3D
data sets (S.sub.1, S.sub.2) relative to one another in such a
manner that voxels are selected in a 3D data set (S.sub.1) and
their location in the other 3D data set (S.sub.2) is determined by
means of a suitable similarity measure, after which X-ray images
(B) are formed from the 3D data sets (S.sub.1, S.sub.2) combined by
means of the transformation rule (F). Consequently, it is possible
to dispense with phantom members that are to be reproduced for fine
adjustment of the individual 3D data sets as well as with manual
fine adjustment steps. The invention also relates to an X-ray
device constructed for this purpose.
Inventors: |
Grass; Michael (Hamburg,
DE), Kemkers; Geerd Richard (Fairfield, CT) |
Assignee: |
Koninklijke Philips Electronics.
N.V. (Eindhoven, NL)
|
Family
ID: |
7627756 |
Appl.
No.: |
09/761,250 |
Filed: |
January 16, 2001 |
Foreign Application Priority Data
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Jan 18, 2000 [DE] |
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100 01 709 |
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Current U.S.
Class: |
378/4; 378/15;
378/8 |
Current CPC
Class: |
G06T
7/32 (20170101); G06T 3/4053 (20130101); A61B
6/027 (20130101); G06T 2207/30004 (20130101) |
Current International
Class: |
G06T
7/00 (20060101); G06T 3/00 (20060101); A61B
006/03 () |
Field of
Search: |
;378/4,8,15,20,98,12,901 |
References Cited
[Referenced By]
U.S. Patent Documents
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|
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5647360 |
July 1997 |
Bani-Hashemi et al. |
5852646 |
December 1998 |
Klotz et al. |
6144759 |
November 2000 |
Weese et al. |
|
Foreign Patent Documents
Other References
"Three-dimensional reconstruction of high contrast objects using
C-arm image intensifier projection data" by M. Grass et al., in
Computerized Medical Imaging and Graphics 23(1999) pp.
311-321..
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Primary Examiner: Bruce; David V.
Attorney, Agent or Firm: Vodopia; John
Claims
What is claimed is:
1. A method of forming X-ray images (B) from at least two series of
projection data sets successively acquired along different
trajectories, a respective 3D data set being formed from each
series of projection data sets and a transformation rule,
describing the location in space of the 3D data sets relative to
one another, being determined in that voxels in one 3D data set are
selected and their location in the other 3D data set is determined
by means of a suitable similarity measure, and X-ray images being
formed from the 3D data sets combined by way of the transformation
rule.
2. A method as claimed in claim 1, wherein a plurality of voxels
are selected in each time a sub-volume of a 3D data set in order to
determine the transformation rule.
3. A method as claimed in claim 1, wherein individual sub-volumes
containing significant image information are selected in order to
determine the transformation rule.
4. A method as claimed in claim 1, wherein the mean absolute
difference, the mean square difference, the double correlation or
the Pearson linear correlation is used as the similarity
measure.
5. A method as claimed in claim 1, wherein the projection data sets
are acquired by means of a C-arm X-ray device or a computed
tomography device.
6. An X-ray device, notably for carrying out the method claimed in
claim 1, which includes an X-ray source and an X-ray detector for
the acquisition of a plurality of series of projection data sets
along different trajectories around an object to be examined, a
reconstruction unit for forming 3D data sets from respective series
of projection data sets, and an arithmetic unit which is
constructed in such a manner that a transformation rule describing
the location in space of the 3D data sets relative to one another
is determined by selecting voxels in a 3D data set and by
determining their location in the other 3D data set by means of a
suitable similarity measure, X-ray images being formed from the 3D
data sets combined by way of the transformation rule.
7. An X-ray device as claimed in claim 6, wherein the X-ray device
is a C-arm X-ray device or a computed tomography device.
Description
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to a method of forming X-ray images from at
least two series of projection data sets successively acquired
along different trajectories, a respective 3D data set being formed
from each series of projection data sets. The invention also
relates to an X-ray device which is particularly suitable for
carrying out this method.
2. Description of the Related Art
A method and a device of this kind are known from EP 860 696 A2.
Therein, two series of projection data sets are acquired along two
semi-circular trajectories by means of a C-arm X-ray device, said
trajectories extending at an angle of 60.degree. relative to one
another. Each series of projection data sets forms a respective 3D
data set wherefrom a respective reconstruction image can be formed.
Because a single 3D data set does not contain adequate data for a
complete and correct reconstruction and artefacts occur during the
reconstruction, the two (or more) 3D data sets are combined by
weighted addition. The desired images are formed from the resultant
data set by reconstruction; artefacts occur to a lesser extent in
said images.
The acquisition of the series of projection data sets along the
different trajectories normally takes place successively in time.
For optimum compatibility of the projection data sets, or the 3D
data sets to be formed therefrom, during the subsequent combination
and reconstruction, it would be necessary for the object to be
examined, for example a patient, to remain motionless during the
data acquisition. In particular the position of the object to be
examined should always be identical during the acquisition of the
individual series of projection data sets and any translatory or
rotary motions of the object to be examined should be as small as
possible. However, because this can hardly be completely achieved
during a practical examination of a patient, it is also known to
reproduce, for example a phantom member in the X-ray images during
the acquisition of the projection data sets; such a phantom can
subsequently be used for fine adjustment so as to achieve matching
3D data sets. This operation is performed by a user.
SUMMARY OF THE INVENTION
Therefore, it is an object of the invention to provide a method
which enables combination of 3D data sets without it being
necessary for a user to perform a fine adjustment operation. It is
also an object to provide an X-ray device which is suitably
constructed for this purpose.
These objects are achieved by means of a method as disclosed in
claim 1 and by means of an X-ray device as disclosed in claim
6.
The invention is based on the recognition of the fact that the same
object to be examined is reproduced in all 3D data sets and that,
therefore, individual structures can be traced in all 3D data sets.
According to the invention this fact is used so as to select the
voxel image values of at least one sub-volume in a first 3D data
set and to search for these values in the other 3D data sets in
order to derive therefrom a transformation rule describing a
translatory or rotary motion, if any, occurring between the
formation of individual 3D data sets. Generally speaking, the
sub-volume V.sub.2 is then selected automatically. The search in
the other 3D data sets for voxels selected in a first 3D data set
utilizes a suitable similarity measure for iteratively finding the
corresponding voxel in the other 3D data sets.
Depending on the desired accuracy, this method can be performed
with the appropriate number of voxels which should be distributed
as well as possible throughout the entire volume represented by the
3D data set. The transformation rule or transformation rules found
are then used to correct for motions of the object to be examined,
to achieve quasi matching of the 3D data sets, to combine them so
as to form a complete data set and to form the desired images
therefrom. According to the method of the invention the foregoing
can be realized without utilizing a phantom object or other markers
reproduced in the X-ray images; the method can be performed
automatically, that is, without interventions by a user.
In order to determine the transformation rule, several voxels
located in respective sub-volumes of a 3D data set and/or
individual voxels containing significant image information are
advantageously selected in conformity with the claims 2 and 3.
Preferably, the functions indicated in claim 4 are used as a
similarity measure. However, other possibilities are also
feasible.
The method according to the invention is used primarily for a C-arm
X-ray device, but can also be used in a computed tomography device;
the invention can also be used notably in an X-ray device or a
computed tomography device involving a conical X-ray beam.
Claim 6 discloses an X-ray device according to the invention which
includes an X-ray source, an X-ray detector, a reconstruction unit
and an arithmetic unit.
BRIEF DESCRIPTION OF THE DRAWINGS
The invention will be described in detail hereinafter with
reference to the drawings. Therein:
FIG. 1 shows a C-arm X-ray device according to the invention,
FIG. 2 illustrates two trajectories,
FIG. 3 shows a block diagram illustrating the method according to
the invention, and
FIG. 4 shows a computed tomography device constructed in accordance
with the invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
The C-arm X-ray device 1 shown in FIG. 1 includes an X-ray tube 2
which is mounted at one end of the C-arm 20 and an X-ray detector 3
which is mounted at the other end of the C-arm 20. The X-ray tube 2
produces a conical X-ray beam 14 which irradiates an object 13 to
be examined, for example, a patient who is arranged on a patient
table 4 in the examination zone, after which the beam is incident
on the two-dimensional X-ray detector 3. The X-ray tube 2 and the
X-ray detector 3 are rotatable about the y axis by way of rails 7
provided on the C-arm 20. Because of the suspension by means of a
plurality of arms and links 5, 6, the position of the C-arm 20 can
be changed in different directions; for example, the C-arm 20 is
capable of rotation about the x, the y and the z axis.
Such motions for the acquisition of projections from different
X-ray positions and the data acquisition are controlled by means of
a control unit 8. The projections acquired are applied to a
reconstruction unit 9 which forms a respective 3D data set, and
possibly therefrom a reconstruction image, from a series of
projections acquired along a trajectory. Such 3D data sets, or the
reconstruction images, are subsequently applied to an arithmetic
unit 10 which determines the transformation rules (or the
transformation parameters for a transformation) between the
individual 3D data sets in conformity with the method of the
invention and ultimately forms the desired X-ray images from the 3D
data sets by means of the transformation rules; the desired X-ray
images can be displayed on a monitor 11.
FIG. 2 shows a sketch illustrating two trajectories T.sub.1 and
T.sub.2. Each trajectory describes the path traveled by the center
of the detector surface of the X-ray detector 3 during the
acquisition of projection data sets. The trajectory is, therefore,
the curve extending through all X-ray positions in which a
respective projection is acquired. In the case shown the
trajectories T.sub.1 and T.sub.2 describe a respective semi-circle
and are tilted through an angle of 2.alpha.=90.degree. relative to
one another. A first 3D data set is acquired from the projections
acquired along the trajectory T.sub.1 whereas a second 3D data set
is formed from the projections acquired along the trajectory
T.sub.2. In order to match these data sets, that is, in order to
eliminate any translatory or rotary motion of the patient occurring
between the acquisition of the first and the second series of
projections, the transformation rule between the two 3D data sets
is subsequently determined as will be described in detail
hereinafter with reference to FIG. 3.
In the block diagram shown in FIG. 3 two sets of projections
P.sub.1 (.alpha..sub.1) and P.sub.2 (.alpha..sub.2) are
symbolically shown as starting points in the blocks 201 and 202;
these two sets have been acquired along two trajectories T.sub.1
and T.sub.2 extending at angles .alpha..sub.1 and .alpha..sub.2,
respectively, relative to a reference plane. In the blocks 211 and
212 a respective 3D data set S.sub.1, S.sub.2 is formed from each
of the projection data sets P.sub.1, P.sub.2.
Subsequently, in the block 22 a transformation rule is determined
from the two 3D data sets S.sub.1, S.sub.2 and is applied to one
(or both) of the two data sets (for example to S.sub.1).
The transformation rule is derived, for example, as follows: a) The
voxels (for example, 16.times.16.times.16) of a sub-volume V.sub.1
(that is, a part of the volume
reproduced by the 3D data set) are selected from one of the two 3D
data sets, for example the data set S.sub.1. This selection can be
performed automatically, for example, by selecting a sub-volume
having an as high as possible contrast (where the voxel image
values in the sub-volume deviate as much as possible from their
mean value). b) Subsequently, the co-ordinates x.sub.1 of the
voxels in the sub-volume V.sub.1 are subjected to a transformation,
for example in conformity with the relation:
where x.sub.1, x.sub.2, u, t are vectors and {character pullout} is
a rotation matrix which describes in the transformation of the
co-ordinates upon a rotation of the co-ordinate system about its
origin. Only the vector x.sub.1 from among the vectors is known
(this is the vector which connects the voxel to the co-ordinate
origin). The vector u represents the co-ordinates of the point
around which the rotation takes place and t is a vector
corresponding to the translation of the voxel. The resultant vector
x.sub.2 represents the co-ordinates of the voxel in the volume
represented by the second 3D data set. When the transformation is
applied to all voxels of the sub-volume, an equally large
sub-volume V.sub.2 will be obtained in the second data set S.sub.2.
c) Subsequently, the correspondence between the voxel image values
of the sub-volume V.sub.2 and the voxel image values of the
sub-volume V.sub.1 of the first 3D data set S.sub.1 is evaluated by
way of a similarity measure. Subsequently, the position and/or the
orientation of the sub-volume selected in the second data set is
varied (by varying u, t, or ) and the similarity between this
sub-volume and the sub-volume V.sub.1 is again evaluated by way of
the similarity measure. These steps are iteratively repeated until
the sub-volume which exhibits the best correspondence to the
sub-volume V.sub.1 of the 3D data set S.sub.1 is found from the 3D
data set S.sub.2. The associated transformation parameters (u, t,
or {character pullout}) then define the transformation rule.
For example, the mean absolute difference MAD of the voxel image
values in the two volumes can be taken as the similarity measure:
##EQU1##
where n is the number of voxels in the sub-volume V.sub.1 or
V.sub.2, and V.sub.1i and V.sub.2i are the i.sup.th voxel image
value in the first sub-volume V.sub.1 and in the second sub-volume
V.sub.2, respectively. Instead of minimizing the mean absolute
difference, for example, the root of the square differences can
also be minimized or the similarity can be evaluated by means of a
suitable correlation coefficient (for example, for a
cross-correlation, double correlation or the Pearson linear
correlation).
The extraction of the transformation parameters from a sub-volume
requires less calculation time than if these parameters were
determined while utilizing all voxel image values of the 3D data
sets. However, it is less accurate and more influenced by noise.
The accuracy can be improved by taking into account two or more
sub-volumes for each 3D data set and by averaging the
transformation parameters found for the various sub-volumes.
The described transformation is based on the assumption that a
rigid object to be examined is present in the examination zone. The
object, however, could also be deformable. The location-dependent
transformation parameters could then be determined by means of a
so-called "elastic matching" method.
In the block 23 an improved 3D data set S is determined from the
transformed 3D data set S.sub.1 and from S.sub.2 by way of
preferably weighted summing of the voxel image values of voxels
which correspond to one another in conformity with the
transformation. As the weighting factor whereby a voxel image value
is multiplied is greater, its distance from the plane defined by
the associated trajectory T.sub.1 or T.sub.2 will be smaller (and
vice versa) and the less the noise and the artefacts will be. This
is because the artefacts in the two 3D data sets S.sub.1 and
S.sub.2 become more manifest in the voxels which are situated
comparatively far from said plane.
FIG. 4 shows a computed tomography device according to the
invention. The X-ray source 2' with a collimator 19 for producing a
conical X-ray beam 15 and the X-ray detector 3' are mounted on a
ring-shaped gantry 18; for the acquisition of projections they
rotate around the object 13 to be examined which is arranged along
the z axis. To this end, the gantry 18 is driven by a motor drive
16 which itself is controlled by a control unit 8'. The projections
acquired are applied to a reconstruction unit 9 for the formation
of 3D data sets and reconstruction images which are applied to the
arithmetic unit 10 again. The formation of the transformation rule
and the subsequent formation of X-ray images take place in
conjunction with the C-arm X-ray device 1 as described above and,
therefore, will not be described again.
The X-ray devices shown are merely examples of embodiments of the
invention. The invention can also be used in other X-ray devices
wherein a complete data set is to be formed from a plurality of 3D
data sets and X-ray images are to be formed therefrom. The
trajectories and their number as shown in FIG. 2 are also given
merely by way of example. The projections can also be acquired
along other trajectories or along more than two trajectories, for
example along two or more parallel full circles or two full circles
extending perpendicularly to one another.
* * * * *